33 citations · 39 across the 5 of their papers we have counts for
5 papers
Bayesian model updating via streamlined Bayesian active learning cubature
Pei-Pei Li, Chao Dang, Cristóbal H. Acevedo +2
This paper proposes a novel Bayesian active learning method for Bayesian model updating, which is termed as "Streamlined Bayesian Active Learning Cubature" (SBALC). The core idea i…
Efficient forward and inverse uncertainty quantification for dynamical systems based on dimension reduction and Kriging surrogate modeling in functional space
Zhouzhou Song, Weiyun Xu, Marcos A. Valdebenito +1
Surrogate models are extensively employed for forward and inverse uncertainty quantification in complex, computation-intensive engineering problems. Nonetheless, constructing high-…
Response probability distribution estimation of expensive computer simulators: A Bayesian active learning perspective using Gaussian process regression
Chao Dang, Marcos A. Valdebenito, Nataly A. Manque +2
Estimation of the response probability distributions of computer simulators in the presence of randomness is a crucial task in many fields. However, achieving this task with guaran…
Sobolev neural network with residual weighting as a surrogate in linear and non-linear mechanics
A. O. M. Kilicsoy, J. Liedmann, M. A. Valdebenito +2
Areas of computational mechanics such as uncertainty quantification and optimization usually involve repeated evaluation of numerical models that represent the behavior of engineer…
First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach
Chen Ding, Chao Dang, Marcos A. Valdebenito +3
First-passage probability estimation of high-dimensional nonlinear stochastic systems is a significant task to be solved in many science and engineering fields, but remains still a…